The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder.
Tiffany Woynaroski, D Kimbrough Oller, Bahar Keceli-Kaysili and 5 others
PMID 27459107WHAT IT FOUND
Automated day-long LENA recordings can produce vocal-development scores that predict later spoken words in preverbal preschoolers with ASD.
A combined IVD plus ACPU-C+V score was not worse than lab samples but was research-only; the commercial AVA DA score did not predict later words.
Key findings
01Automated IVD and ACPU-C+V vocal-development scores predicted later spoken vocabulary and were not significantly different from conventional communication samples.
02The AVA DA score, which can be obtained with standard commercial LENA software, did not predict later spoken vocabulary.
03A combined IVD plus ACPU-C+V score from one day-long recording predicted later spoken vocabulary and was not significantly different from conventional communication samples.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The sample had 20 children, so estimates are imprecise. The prediction was over only 4 months. The best combined automated score was created after the main analyses and was exploratory. The design was longitudinal and correlational, so it cannot show that vocal development causes later spoken vocabulary. The promising IVD and ACPU-C+V scores were not part of the standard commercial LENA package at the time of the study. The sample was preverbal, primarily English-speaking, and excluded severe sensory or motor impairments, so it may not fit all clinical presentations.
The easy way to misread this
Do not conclude that automated LENA vocal scores are ready for routine clinical use or that increasing vocalizations will increase spoken words. The combined score was exploratory, the useful scores were not commercially available, and the commercial AVA DA score did not predict later words.